Field of the Invention
The present invention relates to an image processing apparatus, image processing method, and storage medium for performing a quantization process to form an image on a print medium.
Description of the Related Art
When using a pseudo gradation method to print an image, it is necessary to quantize multi-valued image data, and as a quantization method used for the quantization, an error diffusion method and a dither method are known. In particular, the dither method that compares a preliminarily stored threshold value and a gradation value of multi-valued data to determine dot printing or non-printing is widely used in many image processing apparatuses because a processing load is small as compared with the error diffusion method. Such a dither method has a problem of dot dispersibility in particular in a low gradation range; however, as a threshold value matrix for obtaining preferable dot dispersibility, a threshold value matrix having blue noise characteristics is proposed.
FIGS. 9A to 9C are diagrams for explaining a dither process using a threshold value matrix having blue noise characteristics. FIG. 9A illustrates an example of image data to be inputted into a 10-pixel×10-pixel area. This example shows a state where a gradation value of “36” is inputted into all the pixels. FIG. 9B illustrates a threshold value matrix prepared corresponding to the above 10-pixel×10-pixel area. Each of the pixels is related to any of threshold values of 0 to 254. In the dither method, in the case where a gradation value indicated by multi-valued image data is larger than a threshold value, a corresponding pixel is designated as dot printing “1”. On the other hand, in the case where a gradation value indicated by multi-valued image data is equal to or less than a threshold value, a corresponding pixel is designated as dot non-printing “0”. FIG. 9C illustrates a quantization result based on the dither method. Pixels representing printing “1” are indicated in gray, and pixels representing non-printing “0” are indicated in white. The distribution of printing “1” pixels as seen in FIG. 9C changes depending on threshold value arrangement in the threshold value matrix. By using the threshold value matrix having blue noise characteristics as in FIG. 9B, even in the case where the same pieces of multi-valued data are inputted into a predetermined area as in FIG. 9A, the printing “1” pixels are arranged in a high dispersibility state as in FIG. 9C.
FIGS. 10A and 10B are diagrams illustrating blue noise characteristics and human visual characteristics or a human transfer function (VTF) at a visibility distance of 250 mm. In both of the diagrams, the horizontal axis represents a frequency (cycles/mm), indicating lower and higher frequencies toward the left and right of the graph, respectively. On the other hand, the vertical axis represents intensity (power) corresponding to each frequency.
Referring to FIG. 10A, the blue noise characteristics are characterized by, for example, a suppressed low frequency component, a rapid rise, and a flat high frequency component. Hereinafter, a frequency fg corresponding to a peak resulting from the rapid rise is referred to as a principal frequency. On the other hand, as illustrated in FIG. 10B, the human visual characteristics have high sensitivity in a lower frequency range, but sensitivity in a higher frequency range is low. That is, the lower frequency component is conspicuous, whereas the higher frequency component is inconspicuous. The blue noise characteristics are based on such visual characteristics, and adapted to, in the visual characteristics, hardly has power in the highly sensitive (conspicuous) lower frequency range, but has power in the low sensitive (inconspicuous) higher frequency range. For this reason, when a person visually observes an image subjected to a quantization process using a threshold value matrix having blue noise characteristics, dot deviation or periodicity is unlikely to be perceived, and the image is recognized as a comfortable image.
However, in the quantization process as described above, preferable dispersibility can be obtained for each color material (i.e., each single color); however, when printing an image with multiple color materials (i.e., mixed color), dispersibility may be deteriorated to make graininess conspicuous. This is caused by the fact that threshold value matrices prepared for respective color materials do not have any correlation with one another at all.
U.S. Pat. No. 6,867,884 discloses a dither method for solving such a problem. Specifically, U.S. Pat. No. 6,867,884 discloses a method that prepares one common dither matric having preferable dispersibility as in FIG. 9B, and performs a quantization process while shifting mutual threshold values among multiple colors. According to U.S. Pat. No. 6,867,884 as described, dots having different colors are mutually exclusively printed in a highly dispersible state in a low gradation area, and therefore even in a mixed color image, preferable image quality can be achieved.
However, the method disclosed in U.S. Pat. No. 6,867,884 focuses on the graininess and dispersibility in a mixed color image, but does not focus on a pseudo contour associated with a shift in gradation level. In the following, such a pseudo contour will be described.
In the blue noise characteristics described with FIG. 10A, the principal frequency fg is an average frequency when dispersing a predetermined number of dots as uniformly as possible; however, the principal frequency fg depends on the density of the dots, i.e., gradation.
FIGS. 11A and 11B are diagrams illustrating the relationship between a gradation value (i.e., the dot density) and the principal frequency fg. In FIG. 11A, the horizontal axis represents a gray level g (i.e., the dot density), and the vertical axis represents the principal frequency fg at each gray level. The gray level g is given on the assumption that a state where dots are placed in all pixels in an image area corresponds to “1”, a state where no dots are placed in all the pixels to “0”, and a state where dots are placed in half of the pixels to “½”. The principal frequency fg in this case can be expressed by Expression 1.
                              f          g                =                  {                                                                                          g                                    ⁢                                                          u                                                                                                                    g                  ≤                                      1                    2                                                                                                                                                                  1                      -                      g                                                        ⁢                                                          u                                                                                                                    g                  >                                      1                    2                                                                                                          (                  Expression          ⁢                                          ⁢          1                )            
In Expression 1, u represents the reciprocal of a pixel spacing. As can be seen from FIG. 11A and Expression 1, the principal frequency fg takes the maximum value of fg=√(½)|u| at a gray level of g=½, i.e., when dots are arranged in 50% of the pixels in the entire pixel area. In addition, as the gray level g separates from ½, the principal frequency fg also gradually shifts toward the lower frequency side.
FIG. 11B is a diagram illustrating frequency characteristics in four types of gradation lower than a gray level g of ½ when performing a quantization process using a threshold value matrix having blue noise characteristics, together with the visual characteristics VTF. The diagram illustrates the case where the first gradation has the lowest gray level, and the gray level increases from the second to the third, to the fourth. Blue noise characteristics indicating that a lower frequency component is suppressed, and in a higher frequency range, there is a peak at a principal frequency fg are common to all the types of gradation. However, the principal frequencies fg in the first gradation and the second gradation are present within a range of 2 to 4 cycles/mm, which are also close to the peak of the VTF. That is, a dot pattern in lower gradation has blue noise characteristics, but the dot pattern itself is easily visually perceived.
On the other hand, between the principal frequencies fg in the first gradation and the second gradation, there is a shift of approximately 1 cycles/mm. That is, in a gradation image of which gradation gradually shifts from the first gradation to the second gradation, the shift from a first gradation dot pattern to a second gradation dot pattern is easily visually perceived. For this reason, even in the case where each of the first gradation dot pattern and the second gradation dot pattern is not visually uncomfortable, the discontinuity in dot pattern from the first gradation to the second gradation causes a visually uncomfortable “pseudo contour” to deteriorate image quality.
U.S. Pat. No. 6,867,884 does not focus on any pseudo contour as described above. As a result, U.S. Pat. No. 6,867,884 discloses an embodiment where increasing the dispersibility of a black ink having the highest contrast among multiple color inks is given priority, and black is set for a channel having the lowest threshold value area among multiple channels corresponding to the common threshold value matrix. In this case, if the threshold value matrix has blue noise characteristics, the dot arrangement of the black ink will have blue noise characteristics as described above from lower gradation to higher gradation. As a result, frequency characteristics in a black ink dot patterns will be those as illustrated in FIG. 11B, which may cause the “pseudo contour” to deteriorate image quality.